Merge remote-tracking branch 'upstream/master'

2 files changed, 3 insertions, 3 deletions

diff --git a/training/mira/kbest_cut_mira.cc b/training/mira/kbest_cut_mira.cc
index 62c770df..cde65332 100644
--- a/training/mira/kbest_cut_mira.cc
+++ b/training/mira/kbest_cut_mira.cc
@@ -82,14 +82,14 @@ bool InitCommandLine(int argc, char** argv, po::variables_map* conf) {
     ("optimizer,o",po::value<int>()->default_value(1), "Optimizer (SGD=1, PA MIRA w/Delta=2, Cutting Plane MIRA=3, PA MIRA=4, Triple nbest list MIRA=5)")
     ("fear,f",po::value<int>()->default_value(1), "Fear selection (model-cost=1, maxcost=2, maxscore=3)")
     ("hope,h",po::value<int>()->default_value(1), "Hope selection (model+cost=1, mincost=2)")
-    ("max_step_size,C", po::value<double>()->default_value(0.01), "regularization strength (C)")
+    ("max_step_size,C", po::value<double>()->default_value(0.001), "regularization strength (C)")
     ("random_seed,S", po::value<uint32_t>(), "Random seed (if not specified, /dev/random will be used)")
     ("mt_metric_scale,s", po::value<double>()->default_value(1.0), "Amount to scale MT loss function by")
     ("sent_approx,a", "Use smoothed sentence-level BLEU score for approximate scoring")
     ("pseudo_doc,e", "Use pseudo-document BLEU score for approximate scoring")
     ("no_reweight,d","Do not reweight forest for cutting plane")
     ("no_select,n", "Do not use selection heuristic")
-    ("k_best_size,k", po::value<int>()->default_value(250), "Size of hypothesis list to search for oracles")
+    ("k_best_size,k", po::value<int>()->default_value(500), "Size of hypothesis list to search for oracles")
     ("update_k_best,b", po::value<int>()->default_value(1), "Size of good, bad lists to perform update with")
     ("unique_k_best,u", "Unique k-best translation list")
     ("stream,t", "Stream mode (used for realtime)")
diff --git a/training/mira/mira.py b/training/mira/mira.py
index 0980ef2e..539a0b0e 100755
--- a/training/mira/mira.py
+++ b/training/mira/mira.py
@@ -244,7 +244,7 @@ def evaluate(testset, weights, ini, script_dir, out_dir):
   evaluator = '{}/../utils/decode-and-evaluate.pl'.format(script_dir)
   try:
     p = subprocess.Popen([evaluator, '-c', ini, '-w', weights, '-i', testset, 
-                         '-d', out_dir], stdout=subprocess.PIPE)
+                         '-d', out_dir, '--jobs', args.jobs], stdout=subprocess.PIPE)
     results, err = p.communicate()
     bleu, results = results.split('\n',1)
   except subprocess.CalledProcessError: